Environmental assessment using acoustic complexity indicators

The procedure of sound recording offers new perspectives in ecology. Nevertheless, the existing tools that offer high resolution recordings are expensive. The use of acoustic indicators is proposed as an easy-to-use, rapid, non-intrusive, low-cost option in biodiversity assessment as well as in environmental noise management. The purpose of this research is to evaluate and prioritize acoustic indicators in terms of environmental noise management and biodiversity assessment in order to assist the development of a low cost Automated Recording Unit (ARU). The data collection areas are two similar public spaces of Mytilene, with the only difference being a differentiation regarding the levels of urbanization. A series of sound recordings were performed using a specific protocol. Signal analysis was performed using the R Statistics software. A list of spectral complexity indicators were extracted, evaluated and ranked in order for their incorporation to the ARU created. These indicator results were then visualized using the QGiS software in order to produce sound maps. In conclusion, the complexity indicators are the best solution for both biodiversity assessment and environmental noise management.